Many traditional gas turbine engines utilize data, such as aircraft condition monitoring function data, as the primary source of information to support engine diagnostics. The aircraft condition monitoring function data may consist of discrete data values for various internal temperatures, pressures, and spool speeds, to name a few examples. This data may be captured during various flight phases. Most typically, this data is captured during take-off and stable cruise conditions. Generally, the captured data is corrected for flight condition and ambient environment and then compared to a nominal reference, such as a calibrated model, to produce delta quantities that are trended over time. Anomalous engine behavior may be observed from such trending and noted for further analysis.
Because there may be as little as one data point per flight that is trended, however, it may take several flights to detect a truly deviated condition as opposed to statistical outliers or noise. A fine line exists between alerting to a false alarm from detecting too early and waiting too long to alert, which may result in potential engine faults. For example with respect to cruise conditions, the data is typically single averaged data points and the analysis methods utilized are discrete time methods since trending occurs over numerous flights spanning days, months, and years. As such, a certain level of latency is introduced in observing a shift in a parameter (or a set of parameters) with any degree of persistency as it may take several flights, over a period of days or longer, before a shift could be declared confidently without introducing false alarms that may occur from reacting to single time point outliers.
Furthermore, many condition monitoring systems of legacy gas turbine engines are equipped with continuous recorders, such as quick access recorders, which capture archival data at sampling rates of around 1 Hz. Generally, when the trended aircraft conditioning monitoring function data alerts to an anomalous condition, the continuous recorder data may be used in an investigative diagnosis to aid in identifying the anomaly. If an alert is not noted, however, such continuous recorder data may never be reviewed. While generally effective, such traditional fault detection and identification systems and techniques for gas turbine engines incur added latency in identifying anomalous engine behavior due to trending the once per flight data.